Generative AI will revolutionise how businesses handle data, offering natural language interfaces for queries and merging data and information governance.
Regardless of their current data maturity levels, enterprises often encounter challenges in fully engaging their entire workforce in data-driven decision-making. Senior executives are seeking ways to effectively leverage generative AI to implement enterprise-wide business intelligence, enabling every team to access real-time operational data and derive actionable insights.
IBRS has previously provided research and advisory on digital governance structures and terms of reference. This advisory goes further, examining the issues, content, and agenda of modern digital governance. What should be the focus of IT governance today?
Businesses are shifting from a ‘knowledge’ to an ‘innovation’ economy, with AI driving new ideas, customer engagement, and operational efficiency.
AI video tools, like early desktop publishing, offer huge potential, but smart adoption needs a clear strategy, skilled people, and pilot programmes to ensure real business value.
Most artificial intelligence proof-of-concepts fail in production due to underestimated costs, dynamic data issues, governance, and integration challenges. Tackle these early for success.
Explainable AI offers diverse techniques like LIME, SHAP, and counterfactuals, crucial for building trust, meeting compliance, and empowering staff to collaborate effectively with AI systems.
As AI is progressively being adopted across every industry, organisations need to be more transparent with their stakeholders on how they collect, process and protect their private information.
Salesforce’s Agentforce 3.0 offers new observability for AI agents, but deeper, end-to-end workflow visibility is needed for complex multi-agent systems.
